Software Engineer - GCP, AI

3+ years of experience with Data lakehouse architecture and design, including hands-on experience with Python, pySpark, Kafka, Airflow, Google Cloud Storage, BigQuery, Data Proc, Cloud Composer. 3+ years of experience with Data Lakehouse architecture and design, including hands-on experience with Python, pySpark, Kafka, Airflow, Google Cloud Storage, Big Query, Data Proc, Cloud Composer.

Outstanding long-term contract opportunity! A well-known Financial Services Company is looking for a Software Engineer in Charlotte, NC, Irving, TX, or Phoenix, AZ (Hybrid).

Work with the brightest minds at one of the largest financial institutions in the world. This is a long-term contract opportunity that includes a competitive benefit package! Our client has been around for over 150 years and is continuously innovating in today's digital age. If you want to work for a company that is not only a household name, but also truly cares about satisfying customers' financial needs and helping people succeed financially, apply today.

Contract Duration: 12 Months

Required Skills & Experience

• 4+ years of Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work or consulting experience, training, military experience, education.
• GCP - 5 to 6 yrs.
• AI exposure - 6 months to a year
• Demonstrable skills (recent) using AI tools such as LangChain, LangGraph/ADK, agentic frameworks, RAG, GraphRAG, and using MCP to build agent-based data capabilities
• 5+ years of experience in data engineering including hands-on experience working with Cloud data solutions: creating/supporting Spark based ingestion and processing
• 3+ years of experience with Data Lakehouse architecture and design, including hands-on experience with Python, pySpark, Kafka, Airflow, Google Cloud Storage, Big Query, Data Proc, Cloud Composer
• Hands-on experience developing data flows using Kafka, Flink, and Spark streaming

What You Will Be Doing

• Consult on or participate in moderately complex initiatives and deliverables within Software Engineering and contribute to large-scale planning related to Software Engineering deliverables.
• Review and analyze moderately complex Software Engineering challenges that require an in-depth evaluation of variable factors.
• Contribute to the resolution of moderately complex issues and consult with others to meet Software Engineering deliverables while leveraging solid understanding of the function, policies, procedures, and compliance requirements.
• Collaborate with client personnel in Software Engineering.
• Implement and operationalize modern AI-enabled data capabilities on Google Cloud to ingest, transform, and distribute data for a variety of big data apps
• Leverage AI/Agentic frameworks to automate data management, governance, and data consumption capabilities - data pipelines, data quality, metadata, data compliance, etc.
• Work within a matrix org. with principal engineers, product managers, and data engineers to roadmap, plan, and deliver key data capabilities based on priority
• Demonstrable skills (recent) using AI tools such as LangChain, LangGraph/ADK, agentic frameworks, RAG, GraphRAG, and using MCP to build agent-based data capabilities
• 5+ years of experience in data engineering including hands-on experience working with Cloud data solutions: creating/supporting Spark based ingestion and processing
• 3+ years of experience with Data lakehouse architecture and design, including hands-on experience with Python, pySpark, Kafka, Airflow, Google Cloud Storage, BigQuery, Data Proc, Cloud Composer
• Hands-on experience developing data flows using Kafka, Flink, and Spark streaming